--- title: "{{< iconify ph clipboard-text >}} Performance" format: html --- ```{=html} <script>document.body.classList.add('has-pagination-top');</script> <nav class='pagination-nav pagination-top' role='navigation' aria-label='Page navigation'> <div class='pagination-container'> <button class='pagination-btn pagination-prev pagination-disabled' disabled aria-label='Previous page'> <svg class='pagination-icon' width='18' height='18' viewBox='0 0 20 20' fill='none' xmlns='http://www.w3.org/2000/svg'> <path d='M12 16L6 10L12 4' stroke='currentColor' stroke-width='2' stroke-linecap='round' stroke-linejoin='round'/> </svg> </button> <div class='pagination-info'> <span class='pagination-prefix'>Page </span> <input type='number' class='pagination-input' id='page-input-top' min='1' max='3' value='1' aria-label='Current page'> <span class='pagination-separator'> / 3</span> </div> <a href='performance_p2.html' class='pagination-btn pagination-next' aria-label='Next page'> <svg class='pagination-icon' width='18' height='18' viewBox='0 0 20 20' fill='none' xmlns='http://www.w3.org/2000/svg'> <path d='M8 16L14 10L8 4' stroke='currentColor' stroke-width='2' stroke-linecap='round' stroke-linejoin='round'/> </svg> </a> </div> </nav> <!-- Pagination Navigation Script --> <script> (function() { const pageUrls = ["performance.html","performance_p2.html","performance_p3.html"]; const pageInput = document.getElementById('page-input-top'); if (pageInput) { pageInput.addEventListener('change', function() { const pageNum = parseInt(this.value); if (pageNum >= 1 && pageNum <= pageUrls.length) { window.location.href = pageUrls[pageNum - 1]; } else { this.value = this.getAttribute('value'); } }); pageInput.addEventListener('keypress', function(e) { if (e.key === 'Enter') { this.blur(); } }); } })(); </script> ``` ```{r} #| include: false library (dashboardr)``` ```{r, echo=FALSE} dashboardr::enable_modals() ``` ```{r setup} #| echo: false #| warning: false #| message: false #| error: false #| results: 'hide' # Load required libraries library(dashboardr) library(dplyr) library(highcharter) # Global chunk options knitr::opts_chunk$set( echo = FALSE, warning = FALSE, message = FALSE, error = FALSE, fig.width = 12, fig.height = 8, dpi = 300 ) # Load data from dataset_4014obs.rds data <- readRDS('dataset_4014obs.rds') # Data summary cat('Dataset loaded:', nrow(data), 'rows,', ncol(data), 'columns\n') # Create filtered datasets # Each filter is applied once and reused across visualizations data_filtered_984a0efe <- data %>% dplyr::filter(wave == 1) data_filtered_4af682fd <- data %>% dplyr::filter(wave == 2) ``` ```{r, echo=FALSE, message=FALSE, warning=FALSE, results='asis'} # Use dashboardr's loading overlay function dashboardr::add_loading_overlay("Loading", 1, theme = "light") ``` ```{r, echo=FALSE, results='asis'} cat(as.character(dashboardr::modal_content( modal_id = 'PDCCS1R', text = '<h2>Digital Content Creation: Performance Questions</h2> <img src="https://placehold.co/600x400/EEE/31343C" style="max-width:100%; height:auto;"> <p>Information literacy scores were highest at 85%. Participants excelled at search strategies and source evaluation.</p>' ))) ``` ## {{< iconify ph magnifying-glass >}} Strategic Information ```{r, echo=FALSE, message=FALSE, warning=FALSE} create_blockquote("Performance tasks: proportion correct or selected. Where items are multi-select, we show the share selecting each action.", preset = "question") ``` [ {{< iconify ph cards >}} See all Strategic Information results ](strategic_information.html) ### {{< iconify ph number-circle-one-fill >}} Wave 1 ##### {{< iconify ph users-fill >}} Overall ```{r perf-sis-wave1-overall} # Restrict Google to Dutch sources (correct/incorrect) result <- create_stackedbars( data = data_filtered_984a0efe %>% tidyr::drop_na(PSIS2R), title = "Restrict Google to Dutch sources (correct/incorrect)", questions = "PSIS2R", question_labels = "Restrict Google to Dutch sources (correct/incorrect)", stacked_type = "percent", color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), horizontal = TRUE, x_label = "", stack_breaks = c(0, 10, 20, 30), stack_bin_labels = c("Incorrect", "Correct"), stack_map_values = list("1" = "Correct", "0" = "Incorrect"), stack_order = c("Incorrect", "Correct"), stack_label = NULL, weight_var = "weging_GAMO" ) result ``` ##### {{< iconify mdi:human-male-male-child >}} Age ###### {{< iconify ph chat-circle-fill >}} Question 1 ```{r perf-sis-wave1-age-item1} # Restrict Google to Dutch sources (correct/incorrect) result <- create_stackedbar( data = data_filtered_984a0efe %>% tidyr::drop_na(AgeGroup, PSIS2R), title = "Restrict Google to Dutch sources (correct/incorrect)", stacked_type = "percent", horizontal = TRUE, stack_breaks = c(0, 10, 20, 30), stack_bin_labels = c("Incorrect", "Correct"), stack_map_values = list("1" = "Correct", "0" = "Incorrect"), stack_order = c("Incorrect", "Correct"), color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), weight_var = "weging_GAMO", x_var = "AgeGroup", stack_var = "PSIS2R" ) result ``` ##### {{< iconify mdi gender-transgender >}} Gender ###### {{< iconify ph chat-circle-fill >}} Question 1 ```{r perf-sis-wave1-gender-item1} # Restrict Google to Dutch sources (correct/incorrect) result <- create_stackedbar( data = data_filtered_984a0efe %>% tidyr::drop_na(geslacht, PSIS2R), title = "Restrict Google to Dutch sources (correct/incorrect)", stacked_type = "percent", horizontal = TRUE, stack_breaks = c(0, 10, 20, 30), stack_bin_labels = c("Incorrect", "Correct"), stack_map_values = list("1" = "Correct", "0" = "Incorrect"), stack_order = c("Incorrect", "Correct"), color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), weight_var = "weging_GAMO", x_var = "geslacht", stack_var = "PSIS2R" ) result ``` ##### {{< iconify ph graduation-cap-fill >}} Education ###### {{< iconify ph chat-circle-fill >}} Question 1 ```{r perf-sis-wave1-edu-item1} # Restrict Google to Dutch sources (correct/incorrect) result <- create_stackedbar( data = data_filtered_984a0efe %>% tidyr::drop_na(Education, PSIS2R), title = "Restrict Google to Dutch sources (correct/incorrect)", stacked_type = "percent", horizontal = TRUE, stack_breaks = c(0, 10, 20, 30), stack_bin_labels = c("Incorrect", "Correct"), stack_map_values = list("1" = "Correct", "0" = "Incorrect"), stack_order = c("Incorrect", "Correct"), color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), weight_var = "weging_GAMO", x_var = "Education", stack_var = "PSIS2R" ) result ``` ### {{< iconify ph number-circle-two-fill >}} Wave 2 ##### {{< iconify ph users-fill >}} Overall ```{r perf-sis-wave2-overall} # Restrict Google to Dutch sources (correct/incorrect) result <- create_stackedbars( data = data_filtered_4af682fd %>% tidyr::drop_na(PSIS2R), title = "Restrict Google to Dutch sources (correct/incorrect)", questions = "PSIS2R", question_labels = "Restrict Google to Dutch sources (correct/incorrect)", stacked_type = "percent", color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), horizontal = TRUE, x_label = "", stack_breaks = c(0, 10, 20, 30), stack_bin_labels = c("Incorrect", "Correct"), stack_map_values = list("1" = "Correct", "0" = "Incorrect"), stack_order = c("Incorrect", "Correct"), stack_label = NULL, weight_var = "weging_GAMO" ) result ``` ##### {{< iconify mdi:human-male-male-child >}} Age ###### {{< iconify ph chat-circle-fill >}} Question 1 ```{r perf-sis-wave2-age-item1} # Restrict Google to Dutch sources (correct/incorrect) result <- create_stackedbar( data = data_filtered_4af682fd %>% tidyr::drop_na(AgeGroup, PSIS2R), title = "Restrict Google to Dutch sources (correct/incorrect)", stacked_type = "percent", horizontal = TRUE, stack_breaks = c(0, 10, 20, 30), stack_bin_labels = c("Incorrect", "Correct"), stack_map_values = list("1" = "Correct", "0" = "Incorrect"), stack_order = c("Incorrect", "Correct"), color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), weight_var = "weging_GAMO", x_var = "AgeGroup", stack_var = "PSIS2R" ) result ``` ##### {{< iconify mdi gender-transgender >}} Gender ###### {{< iconify ph chat-circle-fill >}} Question 1 ```{r perf-sis-wave2-gender-item1} # Restrict Google to Dutch sources (correct/incorrect) result <- create_stackedbar( data = data_filtered_4af682fd %>% tidyr::drop_na(geslacht, PSIS2R), title = "Restrict Google to Dutch sources (correct/incorrect)", stacked_type = "percent", horizontal = TRUE, stack_breaks = c(0, 10, 20, 30), stack_bin_labels = c("Incorrect", "Correct"), stack_map_values = list("1" = "Correct", "0" = "Incorrect"), stack_order = c("Incorrect", "Correct"), color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), weight_var = "weging_GAMO", x_var = "geslacht", stack_var = "PSIS2R" ) result ``` ##### {{< iconify ph graduation-cap-fill >}} Education ###### {{< iconify ph chat-circle-fill >}} Question 1 ```{r perf-sis-wave2-edu-item1} # Restrict Google to Dutch sources (correct/incorrect) result <- create_stackedbar( data = data_filtered_4af682fd %>% tidyr::drop_na(Education, PSIS2R), title = "Restrict Google to Dutch sources (correct/incorrect)", stacked_type = "percent", horizontal = TRUE, stack_breaks = c(0, 10, 20, 30), stack_bin_labels = c("Incorrect", "Correct"), stack_map_values = list("1" = "Correct", "0" = "Incorrect"), stack_order = c("Incorrect", "Correct"), color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), weight_var = "weging_GAMO", x_var = "Education", stack_var = "PSIS2R" ) result ``` ### {{< iconify ph chart-line-fill >}} Over Time ##### {{< iconify ph users-fill >}} Overall ###### {{< iconify ph chat-circle-fill >}} Question 1 ```{r perf-sis-overtime-overall-item1} # Restrict Google to Dutch sources (correct/incorrect) result <- create_timeline( data = data, title = "Restrict Google to Dutch sources (correct/incorrect)", time_var = "wave_time_label", chart_type = "line", response_filter = 1, y_min = 0, y_max = 100, response_filter_label = "Percentage who selected/answered correctly", response_filter_combine = TRUE, x_label = "", y_label = "Percentage who selected/answered correctly", color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), weight_var = "weging_GAMO", response_var = "PSIS2R" ) result ``` ##### {{< iconify mdi:human-male-male-child >}} Age ###### {{< iconify ph chat-circle-fill >}} Question 1 ```{r perf-sis-overtime-age-item1} # Restrict Google to Dutch sources (correct/incorrect) result <- create_timeline( data = data, title = "Restrict Google to Dutch sources (correct/incorrect)", time_var = "wave_time_label", chart_type = "line", response_filter = 1, y_min = 0, y_max = 100, x_label = "", y_label = "Percentage who selected/answered correctly", color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), response_filter_label = NULL, weight_var = "weging_GAMO", response_var = "PSIS2R", group_var = "AgeGroup" ) result ``` ##### {{< iconify mdi gender-transgender >}} Gender ###### {{< iconify ph chat-circle-fill >}} Question 1 ```{r perf-sis-overtime-gender-item1} # Restrict Google to Dutch sources (correct/incorrect) result <- create_timeline( data = data, title = "Restrict Google to Dutch sources (correct/incorrect)", time_var = "wave_time_label", chart_type = "line", response_filter = 1, y_min = 0, y_max = 100, x_label = "", y_label = "Percentage who selected/answered correctly", color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), response_filter_label = NULL, weight_var = "weging_GAMO", response_var = "PSIS2R", group_var = "geslacht" ) result ``` ##### {{< iconify ph graduation-cap-fill >}} Education ###### {{< iconify ph chat-circle-fill >}} Question 1 ```{r perf-sis-overtime-edu-item1} # Restrict Google to Dutch sources (correct/incorrect) result <- create_timeline( data = data, title = "Restrict Google to Dutch sources (correct/incorrect)", time_var = "wave_time_label", chart_type = "line", response_filter = 1, y_min = 0, y_max = 100, x_label = "", y_label = "Percentage who selected/answered correctly", color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), response_filter_label = NULL, weight_var = "weging_GAMO", response_var = "PSIS2R", group_var = "Education" ) result ``` ## {{< iconify ph detective-fill >}} Critical Information ```{r, echo=FALSE, message=FALSE, warning=FALSE} create_blockquote("Look closely at this post on social media. What kind of post do you think this is?", preset = "question") ``` [ {{< iconify ph cards >}} See all Critical Information results ](critical_information.html) ### {{< iconify ph number-circle-one-fill >}} Wave 1 ##### {{< iconify ph users-fill >}} Overall ```{r perf-cis-wave1-overall} # result <- create_stackedbars( data = data_filtered_984a0efe %>% tidyr::drop_na(PCIS1R, PCIS2R, PCIS3R), title = "", questions = c("PCIS1R", "PCIS2R", "PCIS3R"), question_labels = c("Classify a social media post (task 1)", "Classify a social media post (task 2)", "What to check for fake news"), stacked_type = "percent", color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), horizontal = TRUE, x_label = "", stack_breaks = c(0, 10, 20, 30), stack_bin_labels = c("Incorrect", "Correct"), stack_map_values = list("1" = "Correct", "0" = "Incorrect"), stack_order = c("Incorrect", "Correct"), stack_label = NULL, weight_var = "weging_GAMO" ) result ``` ##### {{< iconify mdi:human-male-male-child >}} Age ###### {{< iconify ph chat-circle-fill >}} Question 1 ```{r perf-cis-wave1-age-item1} # Classify a social media post (task 1) result <- create_stackedbar( data = data_filtered_984a0efe %>% tidyr::drop_na(AgeGroup, PCIS1R), title = "Classify a social media post (task 1)", stacked_type = "percent", horizontal = TRUE, stack_breaks = c(0, 10, 20, 30), stack_bin_labels = c("Incorrect", "Correct"), stack_map_values = list("1" = "Correct", "0" = "Incorrect"), stack_order = c("Incorrect", "Correct"), color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), weight_var = "weging_GAMO", x_var = "AgeGroup", stack_var = "PCIS1R" ) result ``` ###### {{< iconify ph chat-circle-fill >}} Question 2 ```{r perf-cis-wave1-age-item2} # Classify a social media post (task 2) result <- create_stackedbar( data = data_filtered_984a0efe %>% tidyr::drop_na(AgeGroup, PCIS2R), title = "Classify a social media post (task 2)", stacked_type = "percent", horizontal = TRUE, stack_breaks = c(0, 10, 20, 30), stack_bin_labels = c("Incorrect", "Correct"), stack_map_values = list("1" = "Correct", "0" = "Incorrect"), stack_order = c("Incorrect", "Correct"), color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), weight_var = "weging_GAMO", x_var = "AgeGroup", stack_var = "PCIS2R" ) result ``` ###### {{< iconify ph chat-circle-fill >}} Question 3 ```{r perf-cis-wave1-age-item3} # What to check for fake news result <- create_stackedbar( data = data_filtered_984a0efe %>% tidyr::drop_na(AgeGroup, PCIS3R), title = "What to check for fake news", stacked_type = "percent", horizontal = TRUE, stack_breaks = c(0, 10, 20, 30), stack_bin_labels = c("Incorrect", "Correct"), stack_map_values = list("1" = "Correct", "0" = "Incorrect"), stack_order = c("Incorrect", "Correct"), color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), weight_var = "weging_GAMO", x_var = "AgeGroup", stack_var = "PCIS3R" ) result ``` ##### {{< iconify mdi gender-transgender >}} Gender ###### {{< iconify ph chat-circle-fill >}} Question 1 ```{r perf-cis-wave1-gender-item1} # Classify a social media post (task 1) result <- create_stackedbar( data = data_filtered_984a0efe %>% tidyr::drop_na(geslacht, PCIS1R), title = "Classify a social media post (task 1)", stacked_type = "percent", horizontal = TRUE, stack_breaks = c(0, 10, 20, 30), stack_bin_labels = c("Incorrect", "Correct"), stack_map_values = list("1" = "Correct", "0" = "Incorrect"), stack_order = c("Incorrect", "Correct"), color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), weight_var = "weging_GAMO", x_var = "geslacht", stack_var = "PCIS1R" ) result ``` ###### {{< iconify ph chat-circle-fill >}} Question 2 ```{r perf-cis-wave1-gender-item2} # Classify a social media post (task 2) result <- create_stackedbar( data = data_filtered_984a0efe %>% tidyr::drop_na(geslacht, PCIS2R), title = "Classify a social media post (task 2)", stacked_type = "percent", horizontal = TRUE, stack_breaks = c(0, 10, 20, 30), stack_bin_labels = c("Incorrect", "Correct"), stack_map_values = list("1" = "Correct", "0" = "Incorrect"), stack_order = c("Incorrect", "Correct"), color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), weight_var = "weging_GAMO", x_var = "geslacht", stack_var = "PCIS2R" ) result ``` ###### {{< iconify ph chat-circle-fill >}} Question 3 ```{r perf-cis-wave1-gender-item3} # What to check for fake news result <- create_stackedbar( data = data_filtered_984a0efe %>% tidyr::drop_na(geslacht, PCIS3R), title = "What to check for fake news", stacked_type = "percent", horizontal = TRUE, stack_breaks = c(0, 10, 20, 30), stack_bin_labels = c("Incorrect", "Correct"), stack_map_values = list("1" = "Correct", "0" = "Incorrect"), stack_order = c("Incorrect", "Correct"), color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), weight_var = "weging_GAMO", x_var = "geslacht", stack_var = "PCIS3R" ) result ``` ##### {{< iconify ph graduation-cap-fill >}} Education ###### {{< iconify ph chat-circle-fill >}} Question 1 ```{r perf-cis-wave1-edu-item1} # Classify a social media post (task 1) result <- create_stackedbar( data = data_filtered_984a0efe %>% tidyr::drop_na(Education, PCIS1R), title = "Classify a social media post (task 1)", stacked_type = "percent", horizontal = TRUE, stack_breaks = c(0, 10, 20, 30), stack_bin_labels = c("Incorrect", "Correct"), stack_map_values = list("1" = "Correct", "0" = "Incorrect"), stack_order = c("Incorrect", "Correct"), color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), weight_var = "weging_GAMO", x_var = "Education", stack_var = "PCIS1R" ) result ``` ###### {{< iconify ph chat-circle-fill >}} Question 2 ```{r perf-cis-wave1-edu-item2} # Classify a social media post (task 2) result <- create_stackedbar( data = data_filtered_984a0efe %>% tidyr::drop_na(Education, PCIS2R), title = "Classify a social media post (task 2)", stacked_type = "percent", horizontal = TRUE, stack_breaks = c(0, 10, 20, 30), stack_bin_labels = c("Incorrect", "Correct"), stack_map_values = list("1" = "Correct", "0" = "Incorrect"), stack_order = c("Incorrect", "Correct"), color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), weight_var = "weging_GAMO", x_var = "Education", stack_var = "PCIS2R" ) result ``` ###### {{< iconify ph chat-circle-fill >}} Question 3 ```{r perf-cis-wave1-edu-item3} # What to check for fake news result <- create_stackedbar( data = data_filtered_984a0efe %>% tidyr::drop_na(Education, PCIS3R), title = "What to check for fake news", stacked_type = "percent", horizontal = TRUE, stack_breaks = c(0, 10, 20, 30), stack_bin_labels = c("Incorrect", "Correct"), stack_map_values = list("1" = "Correct", "0" = "Incorrect"), stack_order = c("Incorrect", "Correct"), color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), weight_var = "weging_GAMO", x_var = "Education", stack_var = "PCIS3R" ) result ``` ### {{< iconify ph number-circle-two-fill >}} Wave 2 ##### {{< iconify ph users-fill >}} Overall ```{r perf-cis-wave2-overall} # result <- create_stackedbars( data = data_filtered_4af682fd %>% tidyr::drop_na(PCIS1R, PCIS2R, PCIS3R), title = "", questions = c("PCIS1R", "PCIS2R", "PCIS3R"), question_labels = c("Classify a social media post (task 1)", "Classify a social media post (task 2)", "What to check for fake news"), stacked_type = "percent", color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), horizontal = TRUE, x_label = "", stack_breaks = c(0, 10, 20, 30), stack_bin_labels = c("Incorrect", "Correct"), stack_map_values = list("1" = "Correct", "0" = "Incorrect"), stack_order = c("Incorrect", "Correct"), stack_label = NULL, weight_var = "weging_GAMO" ) result ``` ##### {{< iconify mdi:human-male-male-child >}} Age ###### {{< iconify ph chat-circle-fill >}} Question 1 ```{r perf-cis-wave2-age-item1} # Classify a social media post (task 1) result <- create_stackedbar( data = data_filtered_4af682fd %>% tidyr::drop_na(AgeGroup, PCIS1R), title = "Classify a social media post (task 1)", stacked_type = "percent", horizontal = TRUE, stack_breaks = c(0, 10, 20, 30), stack_bin_labels = c("Incorrect", "Correct"), stack_map_values = list("1" = "Correct", "0" = "Incorrect"), stack_order = c("Incorrect", "Correct"), color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), weight_var = "weging_GAMO", x_var = "AgeGroup", stack_var = "PCIS1R" ) result ``` ###### {{< iconify ph chat-circle-fill >}} Question 2 ```{r perf-cis-wave2-age-item2} # Classify a social media post (task 2) result <- create_stackedbar( data = data_filtered_4af682fd %>% tidyr::drop_na(AgeGroup, PCIS2R), title = "Classify a social media post (task 2)", stacked_type = "percent", horizontal = TRUE, stack_breaks = c(0, 10, 20, 30), stack_bin_labels = c("Incorrect", "Correct"), stack_map_values = list("1" = "Correct", "0" = "Incorrect"), stack_order = c("Incorrect", "Correct"), color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), weight_var = "weging_GAMO", x_var = "AgeGroup", stack_var = "PCIS2R" ) result ``` ###### {{< iconify ph chat-circle-fill >}} Question 3 ```{r perf-cis-wave2-age-item3} # What to check for fake news result <- create_stackedbar( data = data_filtered_4af682fd %>% tidyr::drop_na(AgeGroup, PCIS3R), title = "What to check for fake news", stacked_type = "percent", horizontal = TRUE, stack_breaks = c(0, 10, 20, 30), stack_bin_labels = c("Incorrect", "Correct"), stack_map_values = list("1" = "Correct", "0" = "Incorrect"), stack_order = c("Incorrect", "Correct"), color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), weight_var = "weging_GAMO", x_var = "AgeGroup", stack_var = "PCIS3R" ) result ``` ##### {{< iconify mdi gender-transgender >}} Gender ###### {{< iconify ph chat-circle-fill >}} Question 1 ```{r perf-cis-wave2-gender-item1} # Classify a social media post (task 1) result <- create_stackedbar( data = data_filtered_4af682fd %>% tidyr::drop_na(geslacht, PCIS1R), title = "Classify a social media post (task 1)", stacked_type = "percent", horizontal = TRUE, stack_breaks = c(0, 10, 20, 30), stack_bin_labels = c("Incorrect", "Correct"), stack_map_values = list("1" = "Correct", "0" = "Incorrect"), stack_order = c("Incorrect", "Correct"), color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), weight_var = "weging_GAMO", x_var = "geslacht", stack_var = "PCIS1R" ) result ``` ###### {{< iconify ph chat-circle-fill >}} Question 2 ```{r perf-cis-wave2-gender-item2} # Classify a social media post (task 2) result <- create_stackedbar( data = data_filtered_4af682fd %>% tidyr::drop_na(geslacht, PCIS2R), title = "Classify a social media post (task 2)", stacked_type = "percent", horizontal = TRUE, stack_breaks = c(0, 10, 20, 30), stack_bin_labels = c("Incorrect", "Correct"), stack_map_values = list("1" = "Correct", "0" = "Incorrect"), stack_order = c("Incorrect", "Correct"), color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), weight_var = "weging_GAMO", x_var = "geslacht", stack_var = "PCIS2R" ) result ``` ###### {{< iconify ph chat-circle-fill >}} Question 3 ```{r perf-cis-wave2-gender-item3} # What to check for fake news result <- create_stackedbar( data = data_filtered_4af682fd %>% tidyr::drop_na(geslacht, PCIS3R), title = "What to check for fake news", stacked_type = "percent", horizontal = TRUE, stack_breaks = c(0, 10, 20, 30), stack_bin_labels = c("Incorrect", "Correct"), stack_map_values = list("1" = "Correct", "0" = "Incorrect"), stack_order = c("Incorrect", "Correct"), color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), weight_var = "weging_GAMO", x_var = "geslacht", stack_var = "PCIS3R" ) result ``` ##### {{< iconify ph graduation-cap-fill >}} Education ###### {{< iconify ph chat-circle-fill >}} Question 1 ```{r perf-cis-wave2-edu-item1} # Classify a social media post (task 1) result <- create_stackedbar( data = data_filtered_4af682fd %>% tidyr::drop_na(Education, PCIS1R), title = "Classify a social media post (task 1)", stacked_type = "percent", horizontal = TRUE, stack_breaks = c(0, 10, 20, 30), stack_bin_labels = c("Incorrect", "Correct"), stack_map_values = list("1" = "Correct", "0" = "Incorrect"), stack_order = c("Incorrect", "Correct"), color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), weight_var = "weging_GAMO", x_var = "Education", stack_var = "PCIS1R" ) result ``` ###### {{< iconify ph chat-circle-fill >}} Question 2 ```{r perf-cis-wave2-edu-item2} # Classify a social media post (task 2) result <- create_stackedbar( data = data_filtered_4af682fd %>% tidyr::drop_na(Education, PCIS2R), title = "Classify a social media post (task 2)", stacked_type = "percent", horizontal = TRUE, stack_breaks = c(0, 10, 20, 30), stack_bin_labels = c("Incorrect", "Correct"), stack_map_values = list("1" = "Correct", "0" = "Incorrect"), stack_order = c("Incorrect", "Correct"), color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), weight_var = "weging_GAMO", x_var = "Education", stack_var = "PCIS2R" ) result ``` ###### {{< iconify ph chat-circle-fill >}} Question 3 ```{r perf-cis-wave2-edu-item3} # What to check for fake news result <- create_stackedbar( data = data_filtered_4af682fd %>% tidyr::drop_na(Education, PCIS3R), title = "What to check for fake news", stacked_type = "percent", horizontal = TRUE, stack_breaks = c(0, 10, 20, 30), stack_bin_labels = c("Incorrect", "Correct"), stack_map_values = list("1" = "Correct", "0" = "Incorrect"), stack_order = c("Incorrect", "Correct"), color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), weight_var = "weging_GAMO", x_var = "Education", stack_var = "PCIS3R" ) result ``` ### {{< iconify ph chart-line-fill >}} Over Time ##### {{< iconify ph users-fill >}} Overall ###### {{< iconify ph chat-circle-fill >}} Question 1 ```{r perf-cis-overtime-overall-item1} # Classify a social media post (task 1) result <- create_timeline( data = data, title = "Classify a social media post (task 1)", time_var = "wave_time_label", chart_type = "line", response_filter = 1, y_min = 0, y_max = 100, response_filter_label = "Percentage who selected/answered correctly", response_filter_combine = TRUE, x_label = "", y_label = "Percentage who selected/answered correctly", color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), weight_var = "weging_GAMO", response_var = "PCIS1R" ) result ``` ###### {{< iconify ph chat-circle-fill >}} Question 2 ```{r perf-cis-overtime-overall-item2} # Classify a social media post (task 2) result <- create_timeline( data = data, title = "Classify a social media post (task 2)", time_var = "wave_time_label", chart_type = "line", response_filter = 1, y_min = 0, y_max = 100, response_filter_label = "Percentage who selected/answered correctly", response_filter_combine = TRUE, x_label = "", y_label = "Percentage who selected/answered correctly", color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), weight_var = "weging_GAMO", response_var = "PCIS2R" ) result ``` ###### {{< iconify ph chat-circle-fill >}} Question 3 ```{r perf-cis-overtime-overall-item3} # What to check for fake news result <- create_timeline( data = data, title = "What to check for fake news", time_var = "wave_time_label", chart_type = "line", response_filter = 1, y_min = 0, y_max = 100, response_filter_label = "Percentage who selected/answered correctly", response_filter_combine = TRUE, x_label = "", y_label = "Percentage who selected/answered correctly", color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), weight_var = "weging_GAMO", response_var = "PCIS3R" ) result ``` ##### {{< iconify mdi:human-male-male-child >}} Age ###### {{< iconify ph chat-circle-fill >}} Question 1 ```{r perf-cis-overtime-age-item1} # Classify a social media post (task 1) result <- create_timeline( data = data, title = "Classify a social media post (task 1)", time_var = "wave_time_label", chart_type = "line", response_filter = 1, y_min = 0, y_max = 100, x_label = "", y_label = "Percentage who selected/answered correctly", color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), response_filter_label = NULL, weight_var = "weging_GAMO", response_var = "PCIS1R", group_var = "AgeGroup" ) result ``` ###### {{< iconify ph chat-circle-fill >}} Question 2 ```{r perf-cis-overtime-age-item2} # Classify a social media post (task 2) result <- create_timeline( data = data, title = "Classify a social media post (task 2)", time_var = "wave_time_label", chart_type = "line", response_filter = 1, y_min = 0, y_max = 100, x_label = "", y_label = "Percentage who selected/answered correctly", color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), response_filter_label = NULL, weight_var = "weging_GAMO", response_var = "PCIS2R", group_var = "AgeGroup" ) result ``` ###### {{< iconify ph chat-circle-fill >}} Question 3 ```{r perf-cis-overtime-age-item3} # What to check for fake news result <- create_timeline( data = data, title = "What to check for fake news", time_var = "wave_time_label", chart_type = "line", response_filter = 1, y_min = 0, y_max = 100, x_label = "", y_label = "Percentage who selected/answered correctly", color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), response_filter_label = NULL, weight_var = "weging_GAMO", response_var = "PCIS3R", group_var = "AgeGroup" ) result ``` ##### {{< iconify mdi gender-transgender >}} Gender ###### {{< iconify ph chat-circle-fill >}} Question 1 ```{r perf-cis-overtime-gender-item1} # Classify a social media post (task 1) result <- create_timeline( data = data, title = "Classify a social media post (task 1)", time_var = "wave_time_label", chart_type = "line", response_filter = 1, y_min = 0, y_max = 100, x_label = "", y_label = "Percentage who selected/answered correctly", color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), response_filter_label = NULL, weight_var = "weging_GAMO", response_var = "PCIS1R", group_var = "geslacht" ) result ``` ###### {{< iconify ph chat-circle-fill >}} Question 2 ```{r perf-cis-overtime-gender-item2} # Classify a social media post (task 2) result <- create_timeline( data = data, title = "Classify a social media post (task 2)", time_var = "wave_time_label", chart_type = "line", response_filter = 1, y_min = 0, y_max = 100, x_label = "", y_label = "Percentage who selected/answered correctly", color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), response_filter_label = NULL, weight_var = "weging_GAMO", response_var = "PCIS2R", group_var = "geslacht" ) result ``` ###### {{< iconify ph chat-circle-fill >}} Question 3 ```{r perf-cis-overtime-gender-item3} # What to check for fake news result <- create_timeline( data = data, title = "What to check for fake news", time_var = "wave_time_label", chart_type = "line", response_filter = 1, y_min = 0, y_max = 100, x_label = "", y_label = "Percentage who selected/answered correctly", color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), response_filter_label = NULL, weight_var = "weging_GAMO", response_var = "PCIS3R", group_var = "geslacht" ) result ``` ##### {{< iconify ph graduation-cap-fill >}} Education ###### {{< iconify ph chat-circle-fill >}} Question 1 ```{r perf-cis-overtime-edu-item1} # Classify a social media post (task 1) result <- create_timeline( data = data, title = "Classify a social media post (task 1)", time_var = "wave_time_label", chart_type = "line", response_filter = 1, y_min = 0, y_max = 100, x_label = "", y_label = "Percentage who selected/answered correctly", color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), response_filter_label = NULL, weight_var = "weging_GAMO", response_var = "PCIS1R", group_var = "Education" ) result ``` ###### {{< iconify ph chat-circle-fill >}} Question 2 ```{r perf-cis-overtime-edu-item2} # Classify a social media post (task 2) result <- create_timeline( data = data, title = "Classify a social media post (task 2)", time_var = "wave_time_label", chart_type = "line", response_filter = 1, y_min = 0, y_max = 100, x_label = "", y_label = "Percentage who selected/answered correctly", color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), response_filter_label = NULL, weight_var = "weging_GAMO", response_var = "PCIS2R", group_var = "Education" ) result ``` ###### {{< iconify ph chat-circle-fill >}} Question 3 ```{r perf-cis-overtime-edu-item3} # What to check for fake news result <- create_timeline( data = data, title = "What to check for fake news", time_var = "wave_time_label", chart_type = "line", response_filter = 1, y_min = 0, y_max = 100, x_label = "", y_label = "Percentage who selected/answered correctly", color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), response_filter_label = NULL, weight_var = "weging_GAMO", response_var = "PCIS3R", group_var = "Education" ) result ``` ## {{< iconify ph palette-fill >}} Digital Content Creation ```{r, echo=FALSE, message=FALSE, warning=FALSE} create_blockquote('Which of the <a href="#PDCCS1R" class="modal-link">following icons</a> refer to the function for cutting or removing parts of a picture (\"cropping\")?', preset = 'question') ``` [ {{< iconify ph cards >}} See all Digital Content Creation results ](digital_content_creation.html) ### {{< iconify ph number-circle-one-fill >}} Wave 1 ##### {{< iconify ph users-fill >}} Overall ```{r perf-dccs-wave1-overall} # Identify crop icon result <- create_stackedbars( data = data_filtered_984a0efe %>% tidyr::drop_na(PDCCS1R), title = "Identify crop icon", questions = "PDCCS1R", question_labels = "Identify crop icon", stacked_type = "percent", color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), horizontal = TRUE, x_label = "", stack_breaks = c(0, 10, 20, 30), stack_bin_labels = c("Incorrect", "Correct"), stack_map_values = list("1" = "Correct", "0" = "Incorrect"), stack_order = c("Incorrect", "Correct"), stack_label = NULL, weight_var = "weging_GAMO" ) result ``` ##### {{< iconify mdi:human-male-male-child >}} Age ###### {{< iconify ph chat-circle-fill >}} Question 1 ```{r perf-dccs-wave1-age-item1} # Identify crop icon result <- create_stackedbar( data = data_filtered_984a0efe %>% tidyr::drop_na(AgeGroup, PDCCS1R), title = "Identify crop icon", stacked_type = "percent", horizontal = TRUE, stack_breaks = c(0, 10, 20, 30), stack_bin_labels = c("Incorrect", "Correct"), stack_map_values = list("1" = "Correct", "0" = "Incorrect"), stack_order = c("Incorrect", "Correct"), color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), weight_var = "weging_GAMO", x_var = "AgeGroup", stack_var = "PDCCS1R" ) result ``` ##### {{< iconify mdi gender-transgender >}} Gender ###### {{< iconify ph chat-circle-fill >}} Question 1 ```{r perf-dccs-wave1-gender-item1} # Identify crop icon result <- create_stackedbar( data = data_filtered_984a0efe %>% tidyr::drop_na(geslacht, PDCCS1R), title = "Identify crop icon", stacked_type = "percent", horizontal = TRUE, stack_breaks = c(0, 10, 20, 30), stack_bin_labels = c("Incorrect", "Correct"), stack_map_values = list("1" = "Correct", "0" = "Incorrect"), stack_order = c("Incorrect", "Correct"), color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), weight_var = "weging_GAMO", x_var = "geslacht", stack_var = "PDCCS1R" ) result ``` ##### {{< iconify ph graduation-cap-fill >}} Education ###### {{< iconify ph chat-circle-fill >}} Question 1 ```{r perf-dccs-wave1-edu-item1} # Identify crop icon result <- create_stackedbar( data = data_filtered_984a0efe %>% tidyr::drop_na(Education, PDCCS1R), title = "Identify crop icon", stacked_type = "percent", horizontal = TRUE, stack_breaks = c(0, 10, 20, 30), stack_bin_labels = c("Incorrect", "Correct"), stack_map_values = list("1" = "Correct", "0" = "Incorrect"), stack_order = c("Incorrect", "Correct"), color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), weight_var = "weging_GAMO", x_var = "Education", stack_var = "PDCCS1R" ) result ``` ### {{< iconify ph number-circle-two-fill >}} Wave 2 ##### {{< iconify ph users-fill >}} Overall ```{r perf-dccs-wave2-overall} # Identify crop icon result <- create_stackedbars( data = data_filtered_4af682fd %>% tidyr::drop_na(PDCCS1R), title = "Identify crop icon", questions = "PDCCS1R", question_labels = "Identify crop icon", stacked_type = "percent", color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), horizontal = TRUE, x_label = "", stack_breaks = c(0, 10, 20, 30), stack_bin_labels = c("Incorrect", "Correct"), stack_map_values = list("1" = "Correct", "0" = "Incorrect"), stack_order = c("Incorrect", "Correct"), stack_label = NULL, weight_var = "weging_GAMO" ) result ``` ##### {{< iconify mdi:human-male-male-child >}} Age ###### {{< iconify ph chat-circle-fill >}} Question 1 ```{r perf-dccs-wave2-age-item1} # Identify crop icon result <- create_stackedbar( data = data_filtered_4af682fd %>% tidyr::drop_na(AgeGroup, PDCCS1R), title = "Identify crop icon", stacked_type = "percent", horizontal = TRUE, stack_breaks = c(0, 10, 20, 30), stack_bin_labels = c("Incorrect", "Correct"), stack_map_values = list("1" = "Correct", "0" = "Incorrect"), stack_order = c("Incorrect", "Correct"), color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), weight_var = "weging_GAMO", x_var = "AgeGroup", stack_var = "PDCCS1R" ) result ``` ##### {{< iconify mdi gender-transgender >}} Gender ###### {{< iconify ph chat-circle-fill >}} Question 1 ```{r perf-dccs-wave2-gender-item1} # Identify crop icon result <- create_stackedbar( data = data_filtered_4af682fd %>% tidyr::drop_na(geslacht, PDCCS1R), title = "Identify crop icon", stacked_type = "percent", horizontal = TRUE, stack_breaks = c(0, 10, 20, 30), stack_bin_labels = c("Incorrect", "Correct"), stack_map_values = list("1" = "Correct", "0" = "Incorrect"), stack_order = c("Incorrect", "Correct"), color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), weight_var = "weging_GAMO", x_var = "geslacht", stack_var = "PDCCS1R" ) result ``` ##### {{< iconify ph graduation-cap-fill >}} Education ###### {{< iconify ph chat-circle-fill >}} Question 1 ```{r perf-dccs-wave2-edu-item1} # Identify crop icon result <- create_stackedbar( data = data_filtered_4af682fd %>% tidyr::drop_na(Education, PDCCS1R), title = "Identify crop icon", stacked_type = "percent", horizontal = TRUE, stack_breaks = c(0, 10, 20, 30), stack_bin_labels = c("Incorrect", "Correct"), stack_map_values = list("1" = "Correct", "0" = "Incorrect"), stack_order = c("Incorrect", "Correct"), color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), weight_var = "weging_GAMO", x_var = "Education", stack_var = "PDCCS1R" ) result ``` ### {{< iconify ph chart-line-fill >}} Over Time ##### {{< iconify ph users-fill >}} Overall ###### {{< iconify ph chat-circle-fill >}} Question 1 ```{r perf-dccs-overtime-overall-item1} # Identify crop icon result <- create_timeline( data = data, title = "Identify crop icon", time_var = "wave_time_label", chart_type = "line", response_filter = 1, y_min = 0, y_max = 100, response_filter_label = "Percentage who selected/answered correctly", response_filter_combine = TRUE, x_label = "", y_label = "Percentage who selected/answered correctly", color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), weight_var = "weging_GAMO", response_var = "PDCCS1R" ) result ``` ##### {{< iconify mdi:human-male-male-child >}} Age ###### {{< iconify ph chat-circle-fill >}} Question 1 ```{r perf-dccs-overtime-age-item1} # Identify crop icon result <- create_timeline( data = data, title = "Identify crop icon", time_var = "wave_time_label", chart_type = "line", response_filter = 1, y_min = 0, y_max = 100, x_label = "", y_label = "Percentage who selected/answered correctly", color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), response_filter_label = NULL, weight_var = "weging_GAMO", response_var = "PDCCS1R", group_var = "AgeGroup" ) result ``` ##### {{< iconify mdi gender-transgender >}} Gender ###### {{< iconify ph chat-circle-fill >}} Question 1 ```{r perf-dccs-overtime-gender-item1} # Identify crop icon result <- create_timeline( data = data, title = "Identify crop icon", time_var = "wave_time_label", chart_type = "line", response_filter = 1, y_min = 0, y_max = 100, x_label = "", y_label = "Percentage who selected/answered correctly", color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), response_filter_label = NULL, weight_var = "weging_GAMO", response_var = "PDCCS1R", group_var = "geslacht" ) result ``` ##### {{< iconify ph graduation-cap-fill >}} Education ###### {{< iconify ph chat-circle-fill >}} Question 1 ```{r perf-dccs-overtime-edu-item1} # Identify crop icon result <- create_timeline( data = data, title = "Identify crop icon", time_var = "wave_time_label", chart_type = "line", response_filter = 1, y_min = 0, y_max = 100, x_label = "", y_label = "Percentage who selected/answered correctly", color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), response_filter_label = NULL, weight_var = "weging_GAMO", response_var = "PDCCS1R", group_var = "Education" ) result ``` ## {{< iconify ph chats-fill >}} Netiquette ```{r, echo=FALSE, message=FALSE, warning=FALSE} create_blockquote("Performance tasks: proportion correct or selected. Where items are multi-select, we show the share selecting each action.", preset = "question") ``` [ {{< iconify ph cards >}} See all Netiquette results ](netiquette.html) ### {{< iconify ph number-circle-one-fill >}} Wave 1 ##### {{< iconify ph users-fill >}} Overall ```{r perf-netiquette-wave1-overall} # Ask for Permission to Share result <- create_stackedbars( data = data_filtered_984a0efe %>% tidyr::drop_na(PNS1R), title = "Ask for Permission to Share", questions = "PNS1R", question_labels = "Ask for Permission to Share", stacked_type = "percent", color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), horizontal = TRUE, x_label = "", stack_breaks = c(0, 10, 20, 30), stack_bin_labels = c("Incorrect", "Correct"), stack_map_values = list("1" = "Correct", "0" = "Incorrect"), stack_order = c("Incorrect", "Correct"), stack_label = NULL, weight_var = "weging_GAMO" ) result ``` ##### {{< iconify mdi:human-male-male-child >}} Age ###### {{< iconify ph chat-circle-fill >}} Question 1 ```{r perf-netiquette-wave1-age-item1} # Ask for Permission to Share result <- create_stackedbar( data = data_filtered_984a0efe %>% tidyr::drop_na(AgeGroup, PNS1R), title = "Ask for Permission to Share", stacked_type = "percent", horizontal = TRUE, stack_breaks = c(0, 10, 20, 30), stack_bin_labels = c("Incorrect", "Correct"), stack_map_values = list("1" = "Correct", "0" = "Incorrect"), stack_order = c("Incorrect", "Correct"), color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), weight_var = "weging_GAMO", x_var = "AgeGroup", stack_var = "PNS1R" ) result ``` ##### {{< iconify mdi gender-transgender >}} Gender ###### {{< iconify ph chat-circle-fill >}} Question 1 ```{r perf-netiquette-wave1-gender-item1} # Ask for Permission to Share result <- create_stackedbar( data = data_filtered_984a0efe %>% tidyr::drop_na(geslacht, PNS1R), title = "Ask for Permission to Share", stacked_type = "percent", horizontal = TRUE, stack_breaks = c(0, 10, 20, 30), stack_bin_labels = c("Incorrect", "Correct"), stack_map_values = list("1" = "Correct", "0" = "Incorrect"), stack_order = c("Incorrect", "Correct"), color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), weight_var = "weging_GAMO", x_var = "geslacht", stack_var = "PNS1R" ) result ``` ##### {{< iconify ph graduation-cap-fill >}} Education ###### {{< iconify ph chat-circle-fill >}} Question 1 ```{r perf-netiquette-wave1-edu-item1} # Ask for Permission to Share result <- create_stackedbar( data = data_filtered_984a0efe %>% tidyr::drop_na(Education, PNS1R), title = "Ask for Permission to Share", stacked_type = "percent", horizontal = TRUE, stack_breaks = c(0, 10, 20, 30), stack_bin_labels = c("Incorrect", "Correct"), stack_map_values = list("1" = "Correct", "0" = "Incorrect"), stack_order = c("Incorrect", "Correct"), color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), weight_var = "weging_GAMO", x_var = "Education", stack_var = "PNS1R" ) result ``` ### {{< iconify ph number-circle-two-fill >}} Wave 2 ##### {{< iconify ph users-fill >}} Overall ```{r perf-netiquette-wave2-overall} # Ask for Permission to Share result <- create_stackedbars( data = data_filtered_4af682fd %>% tidyr::drop_na(PNS1R), title = "Ask for Permission to Share", questions = "PNS1R", question_labels = "Ask for Permission to Share", stacked_type = "percent", color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), horizontal = TRUE, x_label = "", stack_breaks = c(0, 10, 20, 30), stack_bin_labels = c("Incorrect", "Correct"), stack_map_values = list("1" = "Correct", "0" = "Incorrect"), stack_order = c("Incorrect", "Correct"), stack_label = NULL, weight_var = "weging_GAMO" ) result ``` ##### {{< iconify mdi:human-male-male-child >}} Age ###### {{< iconify ph chat-circle-fill >}} Question 1 ```{r perf-netiquette-wave2-age-item1} # Ask for Permission to Share result <- create_stackedbar( data = data_filtered_4af682fd %>% tidyr::drop_na(AgeGroup, PNS1R), title = "Ask for Permission to Share", stacked_type = "percent", horizontal = TRUE, stack_breaks = c(0, 10, 20, 30), stack_bin_labels = c("Incorrect", "Correct"), stack_map_values = list("1" = "Correct", "0" = "Incorrect"), stack_order = c("Incorrect", "Correct"), color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), weight_var = "weging_GAMO", x_var = "AgeGroup", stack_var = "PNS1R" ) result ``` ##### {{< iconify mdi gender-transgender >}} Gender ###### {{< iconify ph chat-circle-fill >}} Question 1 ```{r perf-netiquette-wave2-gender-item1} # Ask for Permission to Share result <- create_stackedbar( data = data_filtered_4af682fd %>% tidyr::drop_na(geslacht, PNS1R), title = "Ask for Permission to Share", stacked_type = "percent", horizontal = TRUE, stack_breaks = c(0, 10, 20, 30), stack_bin_labels = c("Incorrect", "Correct"), stack_map_values = list("1" = "Correct", "0" = "Incorrect"), stack_order = c("Incorrect", "Correct"), color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), weight_var = "weging_GAMO", x_var = "geslacht", stack_var = "PNS1R" ) result ``` ##### {{< iconify ph graduation-cap-fill >}} Education ###### {{< iconify ph chat-circle-fill >}} Question 1 ```{r perf-netiquette-wave2-edu-item1} # Ask for Permission to Share result <- create_stackedbar( data = data_filtered_4af682fd %>% tidyr::drop_na(Education, PNS1R), title = "Ask for Permission to Share", stacked_type = "percent", horizontal = TRUE, stack_breaks = c(0, 10, 20, 30), stack_bin_labels = c("Incorrect", "Correct"), stack_map_values = list("1" = "Correct", "0" = "Incorrect"), stack_order = c("Incorrect", "Correct"), color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), weight_var = "weging_GAMO", x_var = "Education", stack_var = "PNS1R" ) result ``` ### {{< iconify ph chart-line-fill >}} Over Time ##### {{< iconify ph users-fill >}} Overall ###### {{< iconify ph chat-circle-fill >}} Question 1 ```{r perf-netiquette-overtime-overall-item1} # Ask for Permission to Share result <- create_timeline( data = data, title = "Ask for Permission to Share", time_var = "wave_time_label", chart_type = "line", response_filter = 1, y_min = 0, y_max = 100, response_filter_label = "Percentage who selected/answered correctly", response_filter_combine = TRUE, x_label = "", y_label = "Percentage who selected/answered correctly", color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), weight_var = "weging_GAMO", response_var = "PNS1R" ) result ``` ##### {{< iconify mdi:human-male-male-child >}} Age ###### {{< iconify ph chat-circle-fill >}} Question 1 ```{r perf-netiquette-overtime-age-item1} # Ask for Permission to Share result <- create_timeline( data = data, title = "Ask for Permission to Share", time_var = "wave_time_label", chart_type = "line", response_filter = 1, y_min = 0, y_max = 100, x_label = "", y_label = "Percentage who selected/answered correctly", color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), response_filter_label = NULL, weight_var = "weging_GAMO", response_var = "PNS1R", group_var = "AgeGroup" ) result ``` ##### {{< iconify mdi gender-transgender >}} Gender ###### {{< iconify ph chat-circle-fill >}} Question 1 ```{r perf-netiquette-overtime-gender-item1} # Ask for Permission to Share result <- create_timeline( data = data, title = "Ask for Permission to Share", time_var = "wave_time_label", chart_type = "line", response_filter = 1, y_min = 0, y_max = 100, x_label = "", y_label = "Percentage who selected/answered correctly", color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), response_filter_label = NULL, weight_var = "weging_GAMO", response_var = "PNS1R", group_var = "geslacht" ) result ``` ##### {{< iconify ph graduation-cap-fill >}} Education ###### {{< iconify ph chat-circle-fill >}} Question 1 ```{r perf-netiquette-overtime-edu-item1} # Ask for Permission to Share result <- create_timeline( data = data, title = "Ask for Permission to Share", time_var = "wave_time_label", chart_type = "line", response_filter = 1, y_min = 0, y_max = 100, x_label = "", y_label = "Percentage who selected/answered correctly", color_palette = c("#3D7271", "#E28D50", "#F5D76E", "#C7E6D5", "#0F6B5A", "#BABACD"), response_filter_label = NULL, weight_var = "weging_GAMO", response_var = "PNS1R", group_var = "Education" ) result ``` ```{=html} <nav class='pagination-nav pagination-bottom' role='navigation' aria-label='Page navigation'> <div class='pagination-container'> <button class='pagination-btn pagination-prev pagination-disabled' disabled aria-label='Previous page'> <svg class='pagination-icon' width='18' height='18' viewBox='0 0 20 20' fill='none' xmlns='http://www.w3.org/2000/svg'> <path d='M12 16L6 10L12 4' stroke='currentColor' stroke-width='2' stroke-linecap='round' stroke-linejoin='round'/> </svg> </button> <div class='pagination-info'> <span class='pagination-prefix'></span> <input type='number' class='pagination-input' id='page-input-bottom' min='1' max='3' value='1' aria-label='Current page'> <span class='pagination-separator'> / 3</span> </div> <a href='performance_p2.html' class='pagination-btn pagination-next' aria-label='Next page'> <svg class='pagination-icon' width='18' height='18' viewBox='0 0 20 20' fill='none' xmlns='http://www.w3.org/2000/svg'> <path d='M8 16L14 10L8 4' stroke='currentColor' stroke-width='2' stroke-linecap='round' stroke-linejoin='round'/> </svg> </a> </div> </nav> <!-- Pagination Navigation Script --> <script> (function() { const pageUrls = ["performance.html","performance_p2.html","performance_p3.html"]; const pageInput = document.getElementById('page-input-bottom'); if (pageInput) { pageInput.addEventListener('change', function() { const pageNum = parseInt(this.value); if (pageNum >= 1 && pageNum <= pageUrls.length) { window.location.href = pageUrls[pageNum - 1]; } else { this.value = this.getAttribute('value'); } }); pageInput.addEventListener('keypress', function(e) { if (e.key === 'Enter') { this.blur(); } }); } })(); </script> ``` 